A deep learning toolbox for automatic segmentation of subcortical limbic structures from MRI images
Year: 2021
Type: article
Abstract: A tool was developed to automatically segment several subcortical limbic structures (nucleus accumbens, basal forebrain, septal nuclei, hypothalamus without mammillary bodies, the mammillary bodies, and fornix) using only a T1-weighted MRI as input. This tool fills an unmet need as there are few, if any, publicly available tools to segment these clinically relevant structures. A U-Net with spatial, intensity, contrast, and noise augmentation was trained using 39 manually labeled MRI data sets. In general, the Dice scores, true positive rates, false discovery rates, and manual-automatic volume correlation were very good relative to comparable tools for other structures. A diverse data set of 698 subjects were segmented using the tool; evaluation of the resulting labelings showed that the tool failed in less than 1% of cases. Test-retest reliability of the tool was excellent. The automatically segmented volume of all structures except mammillary bodies showed effectiveness at detecting either clinical AD effects, age effects, or both. This tool will be publicly released with FreeSurfer (surfer.nmr.mgh.harvard.edu/fswiki/ScLimbic). Together with the other cortical and subcortical limbic segmentations, this tool will allow FreeSurfer to provide a comprehensive view of the limbic system in an automated way.
Source: NeuroImage
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,300
Funders: National Institutes of Health, National Institute on Aging, National Institute of Mental Health, National Institute on Drug Abuse, National Institute of Nursing Research, National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering, National Center for Research Resources, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G104586243, G187944815, G2058387751, G2227408383, Building a pathology-validated neuroimaging tool for Alzheimer's Disease, Computational Imaging Biomarkers of Multiple Sclerosis, G323562261, Segmenting Brain Structures for Neurological Disorders, Cerebrovascular Contributions to Brain Aging and Dementia, Fast motion-robust fetal neuroimaging with MRI, G393103480, Inferring in Vivo Cytoarchitectural Borders in the Medial Temporal Lobe, Algorithms for MR and OCT-based Architectonic and Laminar Segmentation, The Human Connectome Project (HCP), Establishing cellular-validated standards for parcellating hippocampal subfields in aging and Alzheimer's disease, OCTology: histology using optical coherence tomography, Deep Learning Algorithms for FreeSurfer, Vitamin B12 status, cognitive decline and incident dementia, Alzheimer's Disease Neuroimaging Initiative, Nobrainer: A robust and validated neural network tool suite for imagers, Computeserver Structural &Functional Image Analysis, Neuropathology of CTE and Delayed Effects of TBI: Toward In-Vivo Diagnostics, MRI, Genetics & Cognitive Precursors of AD and Dementia, Open-source software for multi-scale mapping of the human brain, Deep Learning Algorithms for FreeSurfer, Software Tools for Automated Modeling of White Matter Fascicles from Diffusion MR, Center for Functional Imaging Technologies, Epidemiology of Dementia in the Framingham Study, A Storage Area Network for Structural and Functional Image Analysis, Precision Monitoring and Assessment in the Framingham Study: Cognitive, MRI, Genetic and Biomarker Precursors of AD & Dementia, Imaging and Analysis Techniques to Construct a Cell Census Atlas of the Human Brain, A Longitudinal Analysis Stream for FreeSurfer, FreeSurfer Development, Maintenance, and Hardening, Center for Mesoscale Mapping, Diagnosing the undiagnosable: studies of Alzheimer disease mimics and confounders via "neuropathometry" of dissection photos with 3D scanning, ABCD-USA Consortium: Data Analysis, Informatics and Resource Center, Silicon Graphics Prism Extreme 128P/1TB
OpenAlex ID: W3203440541